mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-20 21:14:14 +08:00
[Compiled Autograd] Remove duplicate code from double-merge (#106233)
Something awfuly wierd is going on. Somehow the changes in #105808 got applied twice, which caused a lint error on main. Notice how the two block of code are both copies of #105808: Line 273:505dd319ef/test/inductor/test_compiled_autograd.py (L273-L369)Line 372:505dd319ef/test/inductor/test_compiled_autograd.py (L372-L479)Pull Request resolved: https://github.com/pytorch/pytorch/pull/106233 Approved by: https://github.com/malfet
This commit is contained in:
Jason Ansel
committed by
PyTorch MergeBot
PyTorch MergeBot
parent
c11412b4a8
commit
9b94dcf2ac
@ -369,115 +369,6 @@ for name, fn in test_autograd.TestAutograd.__dict__.items():
|
||||
EagerAutogradTests.add_test(name, fn)
|
||||
|
||||
|
||||
def load_test_module(name):
|
||||
testdir = Path(__file__).absolute().parent.parent
|
||||
with mock.patch("sys.path", [*sys.path, str(testdir)]):
|
||||
return SourceFileLoader(
|
||||
name, str(testdir / f"{name.replace('.', '/')}.py")
|
||||
).load_module()
|
||||
|
||||
|
||||
test_autograd = load_test_module("test_autograd")
|
||||
|
||||
|
||||
class EagerAutogradTests(TestCase):
|
||||
@classmethod
|
||||
def add_test(cls, name, fn):
|
||||
@functools.wraps(fn)
|
||||
def wrapped(self: EagerAutogradTests):
|
||||
torch._dynamo.reset()
|
||||
try:
|
||||
with compiled_autograd.enable(compiler_fn):
|
||||
return fn(self)
|
||||
except Exception as e:
|
||||
if not_implemented_re.search(str(e)):
|
||||
raise unittest.SkipTest("not implemented")
|
||||
raise
|
||||
|
||||
if skip_re.match(name) or name in skips or not callable(fn):
|
||||
return
|
||||
elif name.startswith("test"):
|
||||
setattr(cls, name, wrapped)
|
||||
else:
|
||||
setattr(cls, name, fn)
|
||||
|
||||
|
||||
not_implemented_re = re.compile(
|
||||
r"|".join(
|
||||
map(
|
||||
re.escape,
|
||||
[
|
||||
# compiled autograd nyi errors:
|
||||
"compiled_autograd does not support",
|
||||
"not supported by compiled autograd",
|
||||
"not yet implemented for compiled autograd",
|
||||
"not implemented for compiled autograd",
|
||||
"has no attribute '_compiled_autograd_key'",
|
||||
# make_fx() tracing errors:
|
||||
"Cannot access storage of BatchedTensorImpl",
|
||||
"data dependent operator:",
|
||||
],
|
||||
)
|
||||
)
|
||||
)
|
||||
|
||||
# These groups of tests aren't supported yet
|
||||
skip_re = re.compile(r"^test_(sparse|profiler|gradcheck|checkpoint|named_tensor)")
|
||||
|
||||
# Bugs needing investigation:
|
||||
skips = {
|
||||
"test_accumulate_grad_tensor_reference", # torch._dynamo.exc.BackendCompilerFailed: backend='inner_compiler' rai
|
||||
"test_autograd_inplace_views_cross_dtype", # RuntimeError: compiled_args not implemented: torch::autograd::CopyS
|
||||
"test_calculate_shape_util", # AssertionError: NYI: aten._nested_tensor_from_tensor_list.default
|
||||
"test_copy_slices_graph_task_updates", # AssertionError: "Boom!" does not match "compiled_args not implemented:
|
||||
"test_current_graph_task_execution_order", # torch._dynamo.exc.TorchRuntimeError: Failed running call_function <
|
||||
"test_current_node", # RuntimeError: aten::detach() Expected a value of type 'Tensor' for argument 'self' but in
|
||||
"test_dont_materialize_grads", # RuntimeError: compiled_args not implemented: torch::autograd::UndefinedGradBack
|
||||
"test_duplicate_backward_root", # RuntimeError: inserted INTERNAL ASSERT FAILED at "/home/jansel/pytorch/torch/c
|
||||
"test_grad_fn_attr_bindings", # RuntimeError: inserted INTERNAL ASSERT FAILED at "/home/jansel/pytorch/torch/csr
|
||||
"test_grad_unreachable_discovery", # RuntimeError: tensor does not have a device
|
||||
"test_grad_unreachable", # RuntimeError: tensor does not have a device
|
||||
"test_graph_save_on_cpu_cuda", # AssertionError: 0 not greater than 0
|
||||
"test_graph_save_on_cpu", # RuntimeError: inserted INTERNAL ASSERT FAILED at "/home/jansel/pytorch/torch/csrc/dy
|
||||
"test_hooks_cpp", # torch._dynamo.exc.BackendCompilerFailed: backend='inner_compiler' raised:
|
||||
"test_index_backward_does_not_save_tensor", # RuntimeError: expected int but got i0
|
||||
"test_inplace_on_view_weak_grad_fn", # RuntimeError: compiled_args not implemented: torch::autograd::CopySlices
|
||||
"test_input_buffer_accum", # RuntimeError: Cannot access data pointer of Tensor that doesn't have storage
|
||||
"test_integer_outputs", # TypeError: unsupported operand type(s) for +: 'OpOverload' and 'str'
|
||||
"test_leaf_assignment", # RuntimeError: compiled_args not implemented: torch::autograd::CopySlices
|
||||
"test_lobpcg", # RuntimeError: tried to get Double out of SymFloat
|
||||
"test_materialize_grads", # RuntimeError: compiled_args not implemented: torch::autograd::UndefinedGradBackward
|
||||
"test_no_unnecessary_save", # RuntimeError: compiled_args not implemented: torch::autograd::CopyBackwards
|
||||
"test_no_unnecessary_unwrapping", # RuntimeError: inserted INTERNAL ASSERT FAILED at "/home/jansel/pytorch/torch
|
||||
"test_numpy_requires_grad", # AssertionError: "Can't call numpy\(\) on Tensor that requires grad. Use tensor.det
|
||||
"test_pickle", # TypeError: cannot pickle 'StorageWeakRef' object: a class that defines __slots__ without defini
|
||||
"test_reentrant_with_leaf_variable_hook", # RuntimeError: inserted INTERNAL ASSERT FAILED at "/home/jansel/pytor
|
||||
"test_reentrant_with_non_leaf_variable_hook", # RuntimeError: inserted INTERNAL ASSERT FAILED at "/home/jansel/p
|
||||
"test_saved_variable_packing_unpacking_saved_original_with_default_hooks", # RuntimeError: inserted INTERNAL ASS
|
||||
"test_saved_variable_packing_unpacking_saved_original_with_hooks", # RuntimeError: inserted INTERNAL ASSERT FAIL
|
||||
"test_saved_variable_saved_original_inplace_detach", # AssertionError: RuntimeError not raised
|
||||
"test_saving_variable_to_disk", # AttributeError: Can't pickle local object 'WeakValueDictionary.__init__.<local
|
||||
"test_setitem_mask", # torch.fx.experimental.symbolic_shapes.GuardOnDataDependentSymNode: It appears that you're
|
||||
"test_setitem", # RuntimeError: compiled_args not implemented: torch::autograd::CopySlices
|
||||
"test_setting_default_saved_variable_hooks_twice_should_use_inner", # RuntimeError: inserted INTERNAL ASSERT FAI
|
||||
"test_sharded_grad", # RuntimeError: inserted INTERNAL ASSERT FAILED at "/home/jansel/pytorch/torch/csrc/dynamo/
|
||||
"test_tensor_hooks_inplace_over_view", # RuntimeError: compiled_args not implemented: torch::autograd::CopySlic
|
||||
"test_tensor_hooks_inplace", # torch._dynamo.exc.Unsupported: call_function UserDefinedClassVariable() [] {}
|
||||
"test_to_sparse_backward", # torch._dynamo.exc.BackendCompilerFailed: backend='inner_compiler' raised:
|
||||
"test_var_mean_differentiable", # RuntimeError: inserted INTERNAL ASSERT FAILED at "/home/jansel/pytorch/torch/c
|
||||
"test_wrapped_number_saved_variable_hooks", # RuntimeError: this hook should not be called
|
||||
"test_grad_nonleaf_register_hook", # segfault
|
||||
"test_accumulate_grad_with_zero_numel_grad", # aten.sym_size
|
||||
"test_isolated_node", # aten.sym_size
|
||||
}
|
||||
|
||||
if not HAS_CUDA:
|
||||
# Found Tesla M60 which is too old to be supported by the triton GPU compiler
|
||||
skips.add("test_type_conversions")
|
||||
|
||||
for name, fn in test_autograd.TestAutograd.__dict__.items():
|
||||
EagerAutogradTests.add_test(name, fn)
|
||||
|
||||
if __name__ == "__main__":
|
||||
if HAS_CPU:
|
||||
run_tests(needs="filelock")
|
||||
|
||||
Reference in New Issue
Block a user